science writing
I write about science for a range of audiences. On this page, I've chosen three examples of my science writing. Each article was written with a different audience in mind: One was written for New York legislators, one was written for kids and teens, and one was written for scientists. All of these articles were written collaboratively with other people.
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I also publish technical, peer-reviewed manuscripts about my research. If you'd like to read those, check out my Google Scholar page.
This is a knowledge brief I wrote with a group of researchers in the Scientist Action and Advocacy Network, in partnership with public defenders at The Legal Aid Society. It is written primarily for public defenders and legislators but is meant to be accessible to the general public as well. In this brief, we summarize research demonstrating that typical brain and psychological development during adolescence may likely preclude most adolescent waivers from meeting the knowing, intelligent, and voluntary requirements for a valid Miranda waiver. Based on this evidence, we argue that current standard practices regarding Miranda rights in juveniles are not adequately protecting our youth.
This is an article I wrote with my PhD advisor for Frontiers for Young Minds, a journal that is read by kids and teens. This journal is particularly cool because kids and teens are also the reviewers! In this article, we describe different types of emotion regulation, or the strategies we people use to deal with difficult emotions. We also explain ways in which the human brain helps people regulate their emotions.
This is a technical piece written for scientists who are considering analyzing longitudinal data from large, open-source datasets. I wrote this article with other developmental neuroscientists. In this article, we discuss (1) best practices for reproducibility and transparency, (2) the importance of getting to know the data, (3) how the nested structure of longitudinal data can be accounted for in statistical models, and (4) justice, equity, diversity, and inclusion efforts as they pertain to large-scale datasets.
